Signal processing

Basic processing procedures for time series (e.g., performing a z-score of a signal, or filtering a signal).

zscore(signal[, inplace])

Apply a z-score operation to one or several neo.AnalogSignal objects.

cross_correlation_function(signal, channel_pairs)

Computes an estimator of the cross-correlation function (Stoica et al., 2005).

butter(signal[, highpass_frequency, ...])

Butterworth filtering function for neo.AnalogSignal.

wavelet_transform(signal, frequency[, ...])

Compute the wavelet transform of a given signal with Morlet mother wavelet.

hilbert(signal[, padding])

Apply a Hilbert transform to a neo.AnalogSignal object in order to obtain its (complex) analytic signal.

rauc(signal[, baseline, bin_duration, ...])

Calculate the rectified area under the curve (RAUC) for a neo.AnalogSignal.


Calculate the derivative of a neo.AnalogSignal.


[Stoica, 2005]

Petre Stoica, Randolph L Moses, and others. Spectral analysis of signals. Prentice Hall, 2005.

[Le, 2001]

Michel Le Van Quyen, Jack Foucher, Jean-Philippe Lachaux, Eugenio Rodriguez, Antoine Lutz, Jacques Martinerie, and Francisco J Varela. Comparison of hilbert transform and wavelet methods for the analysis of neuronal synchrony. Journal of neuroscience methods, 111(2):83–98, 2001.

[Farge, 1992]

Marie Farge. Wavelet transforms and their applications to turbulence. Annual review of fluid mechanics, 24(1):395–458, 1992.